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Optimization of Aerosol Model Selection for TROPOMI/S5P

Rao, Lanlan and Xu, Jian and Efremenko, Dmitry and Loyola, Diego and Doicu, Adrian (2021) Optimization of Aerosol Model Selection for TROPOMI/S5P. Remote Sensing, 13, p. 2489. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs13132489. ISSN 2072-4292.

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Official URL: https://www.mdpi.com/2072-4292/13/13/2489

Abstract

To retrieve aerosol properties from satellite measurements, micro-physical aerosol models have to be assumed. Due to the spatial and temporal inhomogeneity of aerosols, choosing an appropriate aerosol model is an important task. In this paper, we use a Bayesian algorithm that takes into account model uncertainties to retrieve the aerosol optical depth and layer height from synthetic and real TROPOMI O2A band measurements. The results show that in case of insufficient information for an appropriate micro-physical model selection, the Bayesian algorithm improves the accuracy of the solution.

Item URL in elib:https://elib.dlr.de/142907/
Document Type:Article
Title:Optimization of Aerosol Model Selection for TROPOMI/S5P
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Rao, Lanlanlanlan.rao (at) dlr.deUNSPECIFIED
Xu, Jianjian.xu (at) dlr.dehttps://orcid.org/0000-0003-2348-125X
Efremenko, DmitryDmitry.Efremenko (at) dlr.dehttps://orcid.org/0000-0002-7449-5072
Loyola, DiegoDiego.Loyola (at) dlr.dehttps://orcid.org/0000-0002-8547-9350
Doicu, AdrianAdrian.Doicu (at) dlr.deUNSPECIFIED
Date:June 2021
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:13
DOI :10.3390/rs13132489
Page Range:p. 2489
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Atmosphere Remote Sensing
ISSN:2072-4292
Status:Published
Keywords:TROPOMI, aerosol retrieval, O2A band, Bayesian algorithm
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Spectroscopic methods of the atmosphere
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Efremenko, Dr Dmitry
Deposited On:05 Jul 2021 11:03
Last Modified:24 May 2022 23:47

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